Workflows are tools used to guide any process from start to finish in an organized, predictable fashion. Ideal workflows enhance efficiency while drawing attention to possible areas that may require scrutiny. In general, a workflow is comprised of a series of connected steps, typically automated or semi-automated and processed in sequence. Outputs and/or a subset of outputs from previous steps may be used as inputs in subsequent steps such that each step builds on previous steps. A guided workflow may be comprised of a semi-automated process where manual corrections may be made to the workflow and a sub-sequence of the workflow may be reprocessed. Intrusion (e.g., guiding a workflow) may be triggered, for example, by algorithmic error, inability to capture salient features, failure to output results, etc.
Often, workflows are built around calculating a quantity of interest or preparing preliminary information to provide a foundation for calculating quantities of interest. Such preliminary information may include, for example, a geometric model. In some instances, quantities of interest are especially affected by geometry. For example, quantities of interest including air flow patterns and drag across the wing of an aircraft or exterior shell of an automobile are dependent on model geometry. However, geometries of models may have some uncertainty due, for example, to problems with images from which the models are made. For example, where the images are scans from medical imaging, problems with the images may include motion and registration artifacts, blooming artifacts, etc. Such uncertainty may impact computation of quantities of interest. Geometry sensitivity, then, may be defined as how much uncertainty in geometry may impact the computation of quantities of interest. In other words, sensitivity may describe the extent or amount to which geometry uncertainty affects a quantity of interest calculation.
Thus, a need exists for focusing attention on regions of a model that exhibit higher sensitivity, meaning greater impact on a quantity of interest contributed by uncertainty in geometry. These regions may be specific regions of an image where computations for quantities of interest may be sensitive to reconstructed geometry. A need exists for identifying regions of geometric models based on sensitivity and creating workflows that permit attention to and/or correction of these regions. More specifically, a need exists for guided workflows that may draw attention to highly sensitive regions in a model, for example, in the context of workflows guided by geometry sensitivity.
The foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.